Phylogenomics and systematics of Entomobryoidea (Collembola): marker design, phylogeny and classification.

Entomobryoidea has been the focus of phylogenetic studies in recent years owing to a divergence between morphological and genetic data. Recent phylogenies have converged on the sister relationship of Orchesellidae with the remaining Entomobryoidea, and on the non-monophyly of the traditional Paronellidae and Entomobryidae, but still lack resolution. Known molecular phylogenies of the superfamily differ greatly between mitogenomic and multilocus markers. For this reason, we designed universal single-copy orthologue (USCO) and ultraconserved element (UCE) marker sets specific for Entomobryoidea, based on 11 genome assemblies. Upon the newly designed 3406 USCOs and 4030 UCEs, we analysed 34 species covering all Entomobryoidea families and major subfamilies. New data for 26 species were mined from whole-genome sequencing. Phylogenetic inference confirmed the Orchesellidae as an independent family and the Entomobryinae remained the most puzzling taxon gathering scaled and unscaled lineages of both traditional Entomobryidae and Paronellidae. To accommodate Paronellides, Zhuqinia and related genera, Paronellidinae subfam. nov. is proposed within Entomobryidae. The sampled representatives of Paronellinae were recovered as the sister group of (Seirinae+Lepidocyrtinae), suggesting that reduction on the dorsal macrochaetotaxy and trunk sensillar pattern may have occurred independently within the Lepidocyrtinae and Paronellinae or represent their symplesiomorphy posteriorly modified in the Seirinae. The current systematics of the superfamily are revised here, with Entomobryidae now comprising six subfamilies, including all taxa with smooth dens. Our data also point out that all the main events of cladogenesis of the families and subfamilies of Entomobryoidea occurred during the Jurassic. Our genome-scale phylogenomics provides a complete, reliable example for systematics of Entomobryoidea, as well as other invertebrates in the big data era.